An integrative analysis to reveal that CLEC2B and ferroptosis may bridge the gap between psoriatic arthritis and cancer development

Patients with cutaneous psoriasis (PsC) and psoriatic arthritis (PsA) are reported with increased cancer risk, but the underlying mechanism is less clear, especially the association between the presence of PsA and cancer risk. Motivated by the role of ferroptosis in the progression of cancers as well as inflammation response in psoriasis, this experiment attempts to investigate the relationship between ferroptosis regulators and hub genes in PsA by bioinformatic analysis. The findings revealed an exclusive correlation between CISD1 (ferroptosis regulator) and CLEC2B (hub gene) in PsA group as well as multiple cancer types. Furthermore, CLEC2B was discovered differentially expressed in a variety of cancers and is closely associated with immune cell infiltration as well as immune checkpoints. These results indicate that ferroptosis may act as a bridge between psoriatic arthritis and the onset of certain malignancies.

www.nature.com/scientificreports/ In this study, we set up 2 comparisons including PsA-CL (normal controls) group and PsA-PsC group. Overlapped differentially expressed genes obtained from aforementioned two comparisons were considered as important genes contributed to PsA development, which were used for further analysis [17][18][19] , including GSEA/ DO enrichment analysis, and PPI network construction to obtain hub genes. Subsequently, association analysis of hub genes with differentially expressed ferroptosis regulators was performed. Co-expression interactions in pan-cancer were analyzed using genes with exclusive correlation in PsA to further narrow down the hub genes. CLEC2B, the final standout, was also discovered to be differently expressed in a variety of malignancies and to have a substantial link to prognosis and immune infiltration in a variety of tumors.
As a result, we propose that CLEC2B, via ferroptosis regulators, may be a bridge gene for disease progression and a high cancer risk in psoriatic arthritis.

Materials and methods
The flow chart of this study is shown in Fig. 1. Dataset collection. Gene expression datasets were collected from the Gene Expression Omnibus database (http:// www. ncbi. nlm. nih. gov/ geo) 20 . The uniformly normalized pan-cancer dataset was downloaded from the UCSC (https:// xenab rowser. net/) database 21 : TCGA TARGET GTEx (PANCAN, N = 19,131, G = 60,499). Data processing and differential expression analysis. Raw data were processed and analyzed using R (version 4.0.2) 22 . Firstly, the RMA algorithm 23 was used for background correction and data normalization and the result was show through box plot. Then, the "limma" R package 24 was used to identify DEGs (|Log2FC| ≥ 1, P < 0.05) between each group in the dataset, and a volcano map and heatmap of DEGs was drawn respectively.  www.nature.com/scientificreports/ Functional correlation analysis. Gene Ontology (GO) on DEGs were performed respectively using "clusterProfiler" package 25 . Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using GAGE 26 followed by visualization with the ggplot2 R package 27 . Annotation of the genes and pathways was provided by the KEGG database (http:// www. genome. jp/ kegg) 28 . Disease Ontology (DO) enrichment analysis was performed with an online tool Enrichr (https:// maaya nlab. cloud/ Enric hr/). FDR < 0.05 was considered significant enrichment.

Construction of PPI network.
To characterize the crucial DEGs and clusters in skin scar, we used an online tool STRING (https:// string-db. org/) to construct PPI networks with a minimum required interaction score of 0.4 29 . For further analysis, Cytoscape software 30 was used with the download interaction information. Significant genes were determined by the cytoHubba plugin 31 as hub genes.
Expression patterns analysis of ferroptosis regulators. The list of genes involved in ferroptosis was retrieved from a review on this topic 32 . Then, expression patterns analysis of those ferroptosis regulators were conducted respectively in PsA-PsC and PsA-CL group. The results were shown in box plots, p < 0.05 was considered differentially expressed. The statistical difference of two groups was compared through the Wilcox test.
Association analysis between differentially expressed ferroptosis regulators and hub genes. In order to discover an exclusive link in PsA, an association analysis between those differentially expressed ferroptosis regulators and hub genes was performed in PsA, PsC, and CL group respectively. For detail, all microarray data was downloaded from the GEO database. The raw data were downloaded as MINiML files. The R software pheatmap package was used to draw a multi-gene correlation. The expression correlation of two genes was analyzed with spearman. The abscissa and ordinate represent genes, different colors represent different correlation coefficients (red resents positive correlation whereas blue resents negative correlation), the darker the color, the stronger the relation. Asterisks (*) stand for significance levels, ** for p < 0.01, * for p < 0.05.
Co-expression analysis of target genes in pan-cancer. ENCORI (https:// starb ase. sysu. edu. cn/) 33 was utilized to do a co-expression analysis of target hub genes and major ferroptosis regulators that have exclusive linkages in PsA to further characterize the target genes. Target genes were identified based on the number of cancer species with |co-efficient R| ≥ 0.2 and P < 0.05.

Expression analysis of CLEC2B in pan-cancer.
We extracted the expression data of CLEC2B in various samples and then performed the log2 transformation of each expression value. We calculated the difference in expression between paired tumor and adjacent normal tissues as well as normal and tumor samples in indicated tumor types using R software (version 3.6.4) and analyzed difference significance using unpaired Wilcoxon Rank Sum Tests. Asterisks (*) stand for significance levels, ** for p < 0.01, * for p < 0.05. The results were visualized by ggplot 27 .
Prognostic analysis of CLEC2B in pan-cancer. We obtained a high-quality prognostic dataset of TCGA from previous prognostic studies of TCGA published in Cell 34 . Furthermore, we performed log2(x + 0.001) transformation for each expression value, and finally we also excluded the cancers with less than 10 samples in a single cancer species. The connection between the CLEC2B expression and the prognosis of patients, including overall survival (OS) in multiple types of cancer was examined using forest plots and Kaplan-Meier curves. The hazard ratios (HRs) and 95% confidence intervals were calculated using univariate survival analysis.
Correlation of the CLEC2B expression with immune cell infiltration and immune modulator genes. The gene expression profile of each tumor was extracted and mapped to GeneSymbol. Further, the infiltration score of each immune cell type in each tumor for each patient was re-evaluated based on gene expression, using the xCell 35 and Timer 36 methods of R package IOBR 37 . We calculated spearman's correlation coefficient between gene and immune cell infiltration scores in each tumor using the corr.test function of R package psych (https:// CRAN.R-proje ct. org/ packa ge= psych) to determine the significantly correlated immune infiltration scores. Additionally, the expression data of CLEC2B and 60 marker genes of two types of immune checkpoint pathway genes (Inhibitory(24), Stimulatory(36)) 38 in each sample was also explored, and the spearman correlation between CLEC2B and the marker genes of the five immune pathways was also calculated (*p < 0.05, **p < 0.01, ***p < 0.001).

Results
Data preprocessing. After searching in Gene Expression Omnibus database with the inclusion criteria included: (1) patients with psoriatic arthritis or cutaneous psoriasis; (2) whole blood; 52 blood samples from GSE61281 were obtained (20 from patients with PsA, 20 from patients with PsC and 12 normal controls). We first performed background correction and data normalization after collecting the dataset, and the results are given in box plots ( Fig. 2A,B).

Identification of DEGs.
After data preprocessing, DEGs were identified with the setting of cutoff at P < 0.05 and |log2 (FC)| ≥ 1. As shown in the volcano plots, totally 273 DEGs from PsA-CL group and 86 DEGS from PsA-PsC group were obtained (Fig. 2C,D) www.nature.com/scientificreports/  3C). Further, to study the interaction of overlapped DEGs, the PPI network was built using STRING and then visualized in Cytoscape (Fig. 3D). Subsequently, cytoHubba plugin was used to characterize the hub genes. The top 10 genes based on the filtering algorithm (degree) were shown in Fig. 3E.

Expression profile of selected ferroptosis regulators. Differences in the expression levels of 24
selected ferroptosis regulators were compared between PsA and PsC as well as PsA and CL groups, A difference was deemed significant with P < 0.05 (*p < 0.05, **p < 0.01). Compared with PsC, the expression levels of ACSL4, CISD1, EMC2 and SAT1 were increased in PsA group, but the level of CARS was decreased (Fig. 4B). While compared with CL, the expression level of CISD1, CS, EMC2 were significantly increased (Fig. 4A), while CARS, FDFT1 and HSPA5 were found decreased-expressed. Based on these findings, CISD1, EMC2, and CARS were identified as key ferroptosis regulators that were linked to PsA.
Association analysis of key ferroptosis regulators and hub genes. We then tried to investigate the correlation between 10 hub genes and 3 key ferroptosis regulators with spearman (*p < 0.05, **p < 0.01, ***p < 0.001). As shown in Fig. 4C, in PsA group, among the 3 key ferroptosis regulators, EMC2 showed significantly positive association with all 10 hub genes, CISD1 also showed positive association with 9 hub genes. CARS showed negative association with 3 hub genes (CLEC12B, LPAR6 and UQCRB). As compared to the multiple-gene association results of the PsC group (Fig. 4D) and the CL group (Fig. 4E), CISD1 revealed a distinct positive connection with CLEC12B, CLEC2B, and CSTA exclusively in the PsA group.  www.nature.com/scientificreports/

Pan-cancer co-expression analysis for the ferroptosis regulators-hub genes interactions across 32 types of cancers.
After investigating the pan-cancer section of ENCORI, an online tool, CISD1 was discovered to be highly linked to CLEC2B, CLEC12B and CSTA in a variety of cancer types. We also used |Coefficient-R| ≥ 0.2 as well as p < 0.05 to retrieve the cancer kinds and showed the findings in Fig. 5A. Figure 5B showed the detailed results of each cancer type's co-expression study of CLEC2B. Based on this, we infer that CLEC2B may be the most likely gene associated with ferroptosis in psoriatic arthritis, which is linked to a high risk of cancer.
Functional correlation analysis of CLEC2B and CISD1. GeneMANIA 39 and STRING 29 were used to obtain correlated gene sets of CLEC2B and CISD1 (Fig. 6A,B). Then the two gene lists were used for enrichment analysis, respectively. Enriched GO terms were divided into three categories: molecular function (MF), biological process (BP), and cellular component (CC). The gene list from GeneMANIA was mostly enriched in 'iron-sulfur cluster binding' in the MF group, and 'Oxidative phosphorylation' in the KEGG group, as shown in Fig. 6C. In terms of the STRING gene list, the most prominent results were 'positive regulation of natural killer cell mediated cytotoxicity, immunity' in the BP group, 'iron-sulfur cluster binding' in the MF group, and 'Natural killer cell mediated cytotoxicity' in the KEGG group (Fig. 6D). Prognostic significance of CLEC2B in pan-cancer. We used the coxph function of the R package to build a Cox proportional hazards regression model to analyze the relationship between CLEC2B expression and prognosis in each tumor, and statistical tests were performed using Logrank test to obtain prognostic significance. We finally observed that upregulated CLEC2B expression was remarkably associated with poor OS in 10

Analysis of the CLEC2B expression and immunological correlation in pan-cancer. Among 38
subtypes of immune cells, we found that the CLEC2B expression significantly correlated with most subtypes in different tumor types (Fig. 9). As shown in Fig. 10A, the expression of CLEC2B was significantly associated with the abundance of infiltrating immune cells using TIMER method: B cells in 24 types of cancer, CD4+ T cells in 29 types of cancer, CD8+ T cells in 30 types of cancer, neutrophils in 34 types of cancer, macrophages in 33 types of cancer, and DCs in 33 types of cancer. We further used the deconvo_xCell method of the R package IOBR to calculate the infiltration scores of various types of immune cells. Immunosurveillance influences the prognosis of cancer patients, and tumors evade immune responses by taking advantage of immune checkpoints. Our findings revealed that CLEC2B was correlated with most immunoinhibitors and immunostimulators in multiple cancer types (Fig. 10B), suggesting that CLEC2B could collectively influence the prognosis of multiple cancers through immunosurveillance.

Discussion
The risk of cancer developing and incidence in people with psoriasis disease has raised some concern 40,41 . Contrary to the established nature of the associations between these comorbidities including depression and cardiovascular disease, the underlying mechanism of high cancer risk and psoriasis disease appear to be much less well-established 42 . Even less is known about whether psoriatic arthritis raises the risk of cancer in psoriasis sufferers. Given the importance of ferroptosis in cancer development as well as inflammatory response in psoriasis 43 ,   www.nature.com/scientificreports/ we attempted to employ bioinformatics analysis to investigate the association between ferroptosis and psoriasis disease, specifically psoriatic arthritis. In this investigation, a total of 10 hub genes (Fig. 3E) and 3 differentially expressed ferroptosis regulators (CISD1, EMC2, CARS) were obtained through a series of analysis. Going to follow that, association analysis was performed for the aforementioned genes. The results revealed that CISD1 was associated with CLEC12B, CLEC2B and CSTA only in PsA. We therefore postulate that the four genes could serve as distinctive indicators that distinguish psoriatic arthritis from cutaneous psoriasis. Among them, CISD1 was also found to be closely linked to CLEC12B, CLEC2B and CSTA in a variety of cancers, with CLEC2B being involved in the largest number of cancer types. CLEC2B, a member of the C-type lectin domain family 2 (CLEC-2) that was formerly known as activation-induced C-type lectin (AICL), is a protein encoded by the natural killer (NK) gene complex proximal CD69 that has a high level of expression during lymphocyte activation 44 . Our results similarly demonstrate the relationship between CLEC2B and natural killer cells. Additionally, we discovered that CLEC2B collaborated with the ferroptosis regulator CISD1 to connect iron-sulfer cluster binding and oxidative phosphorylation, further demonstrating the strong connection between CLEC2B and ferroptosis.
Based on aforementioned results, we further explored the function of CELC2B in pan-cancer. In previous studies, CLEC2B has been identified as a marker for a variety of cancers, including clear cell renal cell carcinoma, melanoma, and pancreatic adenocarcinoma 45,46 . Similar to the findings of prior studies, this study found vital functions for CLEC2B in numerous cancers, including changes in expression, correlation with prognosis, infiltration of multiple immune cells and even immune checkpoints in multiple cancer types. Given that, CLEC2B was considered as a key gene which bridges the gap between the development of psoriatic arthritis and cancer through ferroptosis. However, the link between CLEC2B and ferroptosis regulator CISD1 in various malignancies varied in strength and type, which implies that even the same two genes function differently under various regulatory systems in malignant tumors, demonstrating the complexity and unknowable nature of cancer etiology. This is the first time that CLEC2B has been found to be associated with the development of psoriatic arthritis through natural killer cells. More importantly, as a key gene exclusively linked to ferroptosis regulators in psoriatic arthritis, CLEC2B is differentially expressed in a variety of cancers and is closely associated with immune cell infiltration as well as immune checkpoints. This study may provide new research insights into the high cancer risk in patients with psoriatic psoriasis.